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An environmental Luenberger–Hicks–Moorsteen total factor productivity indicator: empirical analysis considering undesirable outputs either as inputs or outputs, and attention for infeasibilities

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  • Zhiyang Shen

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Kristiaan Kerstens

    (LEM - Lille économie management - UMR 9221 - UA - Université d'Artois - UCL - Université catholique de Lille - Université de Lille - CNRS - Centre National de la Recherche Scientifique)

  • Tomas Baležentis

    (Vilnius University [Vilnius])

Abstract

The measurement of economic growth is important for identifying the development patterns followed by different economies. In the light of sustainable development goals, one needs to be able to track the green growth, i.e., they must the adjusted in regard to generation of undesirable outputs that are usually non-marketed. This contribution puts forward an empirical case of the economically developed countries grouped in OECD and measures their total factor productivity (TFP) growth. This is done by exploiting a novel formulation of the Luenberger–Hicks–Moorsteen (LHM) TFP indicator based on the Kuosmanen (Am J Agric Econ 87(4):1077–1082, 2005) proposal. We argue that undesirable outputs must be regarded as special outputs but not inputs in both the production technology and TFP measure. We compare two models: one that considers undesirable outputs as special outputs in the directional distance functions of TFP indicator following Kuosmanen (Am J Agric Econ 87(4):1077–1082, 2005), and another that considers undesirable outputs as inputs following Abad (J Environ Manage 161:325–334, 2015). This proposed approach assumes that input- and output-orientations are taken, with the latter handling both desirable and undesirable outputs simultaneously. Still, we compare our results with those based on the other more conventional frameworks. The empirical case deals with OECD country-level data for 1991–2019. The results suggest that there exist substantial differences in the resulting measures of the TFP growth depending on the distance functions used in the calculation of the LHM indicator.

Suggested Citation

  • Zhiyang Shen & Kristiaan Kerstens & Tomas Baležentis, 2023. "An environmental Luenberger–Hicks–Moorsteen total factor productivity indicator: empirical analysis considering undesirable outputs either as inputs or outputs, and attention for infeasibilities," Post-Print hal-04273656, HAL.
  • Handle: RePEc:hal:journl:hal-04273656
    DOI: 10.1007/s10479-023-05482-4
    Note: View the original document on HAL open archive server: https://hal.science/hal-04273656
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    References listed on IDEAS

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    1. Diewert, W. Erwin & Fox, Kevin J., 2014. "Reference technology sets, Free Disposal Hulls and productivity decompositions," Economics Letters, Elsevier, vol. 122(2), pages 238-242.
    2. Robert C. Feenstra & Robert Inklaar & Marcel P. Timmer, 2015. "The Next Generation of the Penn World Table," American Economic Review, American Economic Association, vol. 105(10), pages 3150-3182, October.
    3. Chen, Jiandong & Wang, Ping & Cui, Lianbiao & Huang, Shuo & Song, Malin, 2018. "Decomposition and decoupling analysis of CO2 emissions in OECD," Applied Energy, Elsevier, vol. 231(C), pages 937-950.
    4. Po-Chi Chen & Ming-Miin Yu, 2014. "Total factor productivity growth and directions of technical change bias: evidence from 99 OECD and non-OECD countries," Annals of Operations Research, Springer, vol. 214(1), pages 143-165, March.
    5. W. Briec & K. Kerstens, 2009. "Infeasibility and Directional Distance Functions with Application to the Determinateness of the Luenberger Productivity Indicator," Journal of Optimization Theory and Applications, Springer, vol. 141(1), pages 55-73, April.
    6. repec:bla:scandj:v:98:y:1996:i:2:p:303-13 is not listed on IDEAS
    7. Ang, Frederic & Kerstens, Pieter Jan, 2020. "A superlative indicator for the Luenberger-Hicks-Moorsteen productivity indicator: Theory and application," European Journal of Operational Research, Elsevier, vol. 285(3), pages 1161-1173.
    8. Arnaud Abad, 2015. "An environmental generalised Luenberger-Hicks-Moorsteen productivity indicator and an environmental generalised Hicks-Moorsteen productivity index," Post-Print hal-03025374, HAL.
    9. Walter Briec & Kristiaan Kerstens, 2004. "A Luenberger-Hicks-Moorsteen productivity indicator: its relation to the Hicks-Moorsteen productivity index and the Luenberger productivity indicator," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 23(4), pages 925-939, May.
    10. Jeanneaux, Philippe & Latruffe, Laure, 2016. "Modelling pollution-generating technologies in performance benchmarking: Recent developments, limits and future prospects in the nonparametric frameworkAuthor-Name: Dakpo, K. Hervé," European Journal of Operational Research, Elsevier, vol. 250(2), pages 347-359.
    11. Robert G. Chambers, 2002. "Exact nonradial input, output, and productivity measurement," Economic Theory, Springer;Society for the Advancement of Economic Theory (SAET), vol. 20(4), pages 751-765.
    12. Beltrán-Esteve, Mercedes & Picazo-Tadeo, Andrés J., 2017. "Assessing environmental performance in the European Union: Eco-innovation versus catching-up," Energy Policy, Elsevier, vol. 104(C), pages 240-252.
    13. Fare, Rolf & Grosskopf, Shawna & Noh, Dong-Woon & Weber, William, 2005. "Characteristics of a polluting technology: theory and practice," Journal of Econometrics, Elsevier, vol. 126(2), pages 469-492, June.
    14. Diewert, W. Erwin & Fox, Kevin J., 2017. "Decomposing productivity indexes into explanatory factors," European Journal of Operational Research, Elsevier, vol. 256(1), pages 275-291.
    15. Caves, Douglas W & Christensen, Laurits R & Diewert, W Erwin, 1982. "The Economic Theory of Index Numbers and the Measurement of Input, Output, and Productivity," Econometrica, Econometric Society, vol. 50(6), pages 1393-1414, November.
    16. Walter Briec & Kristiaan Kerstens, 2011. "The Hicks–Moorsteen Productivity Index Satisfies The Determinateness Axiom," Manchester School, University of Manchester, vol. 79(4), pages 765-775, July.
    17. Massimo Del Gatto & Adriana Di Liberto & Carmelo Petraglia, 2011. "Measuring Productivity," Journal of Economic Surveys, Wiley Blackwell, vol. 25(5), pages 952-1008, December.
    18. Atkinson, Scott E & Cornwell, Christopher & Honerkamp, Olaf, 2003. "Measuring and Decomposing Productivity Change: Stochastic Distance Function Estimation versus Data Envelopment Analysis," Journal of Business & Economic Statistics, American Statistical Association, vol. 21(2), pages 284-294, April.
    19. Ang, Frederic & Kerstens, Pieter Jan, 2017. "Decomposing the Luenberger–Hicks–Moorsteen Total Factor Productivity indicator: An application to U.S. agriculture," European Journal of Operational Research, Elsevier, vol. 260(1), pages 359-375.
    20. Chen, Bin & Jin, Yingmei, 2020. "Adjusting productivity measures for CO2 emissions control: Evidence from the provincial thermal power sector in China," Energy Economics, Elsevier, vol. 87(C).
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